In order to improve the real-time performance, state estimation accuracy and intelligence degree of vehicle power battery pack monitoring system, a monitoring system architecture of vehicle power battery pack based on cloud-edge collaboration is proposed. By deeply integrating edge computing real-time response with cloud big data analysis capabilities, a multi-level collaborative monitoring system is built. The system utilizes STM32 series chips to build a high-precision hardware architecture, integrating data acquisition, equalization control, insulation detection, and 5G networking location modules. An innovative dynamic compensation open circuit voltage-ampere hour integration algorithm is proposed, incorporating multi-parameter correction mechanisms including temperature and cycle count, achieving SOC estimation error ≤±1.2%. The experimental results demonstrate that the system achieves dynamic accuracies of ±0.11% for voltage acquisition and ±0.4% for current acquisition, with cell voltage variance reduced by 99.1% after equalization. The key indicators are superior to the national standard requirements. This research provides a cloud-edge collaborative solution with high-precision, low latency, and scalability for vehicle batteries safety management. The system has certain engineering application value.